code: def model_creator(config):
      return CustomizedNet(
          dropout=config["dropout"],
          input_size=config["past_seq_len"],
          input_feature_num=config["input_feature_num"],
          hidden_dim=config["hidden_dim"],
          output_size=config["output_feature_num"],
      )
  
imports: from unittest import TestCase
  import pytest
  import torch
  import torch.nn
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  from zoo.chronos.autots import AutoTSEstimator, TSPipeline
  from zoo.chronos.data import TSDataset
  from zoo.orca.automl import hp
  import pandas
label_desc: Use image node_id 4 for calling a global function with example usage: model_creator(config) and returns: CustomizedNet